Histology-specific standardized incidence ratio improves the estimation of second primary lung cancer risk

Background Lung cancer (LC) survivors are at increased risk for developing a second primary cancer (SPC) compared to the general population. While this risk is particularly high for smoking-related SPCs, the published standardized incidence ratio (SIR) for lung cancer after lung cancer is unexpectedly low in countries that follow international multiple primary (IARC/IACR MP) rules when compared to the USA, where distinct rules are employed. IARC/IACR rules rely on histology-dependent documentation of SPC with the same location as the first cancer and only classify an SPC when tumors present different histology. Thus, SIR might be underestimated in cancer registries using these rules. This study aims to assess whether using histology-specific reference rates for calculating SIR improves risk estimates for second primary lung cancer (SPLC) in LC survivors. Methods We (i) use the distribution of histologic subtypes of LC in population-based cancer registry data of 11 regional cancer registries from Germany to present evidence that the conventional SIR metric underestimates the actual risk for SPLC in LC survivors in registries that use IARC/IACR MP rules, (ii) present updated risk estimates for SPLC in Germany using a novel method to calculate histological subtype-specific SIRs, and (iii) validate this new method using US SEER (Surveillance, Epidemiology, and End Results Program) data, where different MP rules are applied. Results The adjusted relative risk for lung cancer survivors in Germany to develop an SPLC was 2.98 (95% CI 2.53–3.49) for females and 1.15 (95% CI 1.03–1.27) for males using the novel histology-specific SIR. When using IARC/IACR MP rules, the conventional SIR underestimates the actual risk for SPLC in LC survivors by approximately 30% for both sexes. Conclusions Our proposed histology-specific method makes the SIR metric more robust against MP rules and, thus, more suitable for cross-country comparisons. Supplementary Information The online version contains supplementary material available at 10.1186/s12916-024-03398-9.

Table S2: Details of dataset filtering Table S3: Details of data modifications Table S4: Data quality for included regions and SIR estimates Table S5: Conversion table of histology codes into ICD-O-3 histologically 'different' groups and histological subtypes of lung cancer Section S6: Details on simulations to estimate the size of bias using standard SIR We simulate various scenarios to estimate the size of bias introduced by using general population reference rates for calculating SIR of same-site SPC when IARC/IACR MP rules are applied.First, we assume that the baseline risk of LC survivors to develop an SPLC is the same as for the general population (real SIR = 1.0).We determined the proportions of histologically different LC groups  ℎ  in the analysis dataset for all index LC cases aged 30 to 99 years and excluded death certificate only (DCO) diagnoses.Then, we assumed that the SPLC would have the same histology group distribution as the first cancer.We expect the true SIR to be the fraction of observed and expected cases.In the case of the no risk difference between LC survivors and the general population   , the count of observed cases   equals the number of expected cases (as the product of person-years at risk   and general population reference rates   ) for each specific stratum .We always stratified SIR in our analyses by age, sex, region, and period using stratum-specific reference rates for the general population.
Then, we take into account that there is a correction factor  ℎ for combinations of LC and SPLC that are not possible in our observed cases according to IARC/IACR MP rules.Suppose we assume that the SPLC would have the same histology group distribution as for the first cancer, and any histology group A can only be followed by a histology group, not A. In that case, the correction factor is 1 −  ℎ  .This gives for the simulated SIR under IARC/IACR MP rules: The factor  ℎ  is sex-and histology-specific, but the same for all age-groups and regions.
Generalized for any given   , the simulation would give

Figure S7 :
Figure S7: Histological groups of LC and SPLC Additionally to the scenario of no risk difference (  = 1.0), we also simulate a true doubling of SPLC risk for LC survivors (  = 2.0) and a risk increase comparable to data of U.S. lung cancer survivors for males (  = 3.38) and females (  = 4.85) published by Thakur et al.

Table S10 :
Sensitivity analysis A -Risk of SPLC using unadjusted and histology-specific SIR method [restricted to six German PBCR with low DCO rate]